Overview

Dataset statistics

Number of variables13
Number of observations323
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.9 KiB
Average record size in memory104.4 B

Variable types

Numeric13

Warnings

LOAD is highly correlated with AIR FLOWHigh correlation
AIR FLOW is highly correlated with LOAD High correlation
APH-A-inlet-O2 is highly correlated with APH-B-inlet-O2 and 2 other fieldsHigh correlation
APH-B-inlet-O2 is highly correlated with APH-A-inlet-O2High correlation
APH-A-outlet-O2 is highly correlated with APH-A-inlet-O2 and 1 other fieldsHigh correlation
APH-B-outlet-O2 is highly correlated with APH-A-inlet-O2 and 1 other fieldsHigh correlation
APH OUTLET TEMP-PASSA is highly correlated with APH OUTLET TEMP-PASSBHigh correlation
APH OUTLET TEMP-PASSB is highly correlated with APH OUTLET TEMP-PASSAHigh correlation
df_index is uniformly distributed Uniform
df_index has unique values Unique
LOAD has unique values Unique
COAL FLOW has unique values Unique
APH-A-inlet-O2 has unique values Unique
APH-B-inlet-O2 has unique values Unique
APH-A-outlet-O2 has unique values Unique
APH-B-outlet-O2 has unique values Unique
APH OUTLET TEMP-PASSA has unique values Unique
APH OUTLET TEMP-PASSB has unique values Unique

Reproduction

Analysis started2022-09-21 13:36:15.761222
Analysis finished2022-09-21 13:36:31.703680
Duration15.94 seconds
Software versionpandas-profiling v2.12.0
Download configurationconfig.yaml

Variables

df_index
Real number (ℝ≥0)

UNIFORM
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162
Minimum1
Maximum323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:31.788678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.1
Q181.5
median162
Q3242.5
95-th percentile306.9
Maximum323
Range322
Interquartile range (IQR)161

Descriptive statistics

Standard deviation93.3862945
Coefficient of variation (CV)0.576458608
Kurtosis-1.2
Mean162
Median Absolute Deviation (MAD)81
Skewness0
Sum52326
Variance8721
MonotonicityStrictly increasing
2022-09-21T19:06:31.912713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
0.3%
2431
 
0.3%
2211
 
0.3%
2201
 
0.3%
2191
 
0.3%
2181
 
0.3%
2171
 
0.3%
2161
 
0.3%
2151
 
0.3%
2141
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
11
0.3%
21
0.3%
31
0.3%
41
0.3%
51
0.3%
ValueCountFrequency (%)
3231
0.3%
3221
0.3%
3211
0.3%
3201
0.3%
3191
0.3%

DUST
Real number (ℝ≥0)

Distinct108
Distinct (%)33.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.99077399
Minimum30
Maximum329
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:32.044199image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile36
Q146
median68
Q3102
95-th percentile167.6
Maximum329
Range299
Interquartile range (IQR)56

Descriptive statistics

Standard deviation44.3386767
Coefficient of variation (CV)0.5542973831
Kurtosis5.030811717
Mean79.99077399
Median Absolute Deviation (MAD)26
Skewness1.783696657
Sum25837.02
Variance1965.918251
MonotonicityNot monotonic
2022-09-21T19:06:32.160197image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3715
 
4.6%
389
 
2.8%
519
 
2.8%
599
 
2.8%
349
 
2.8%
368
 
2.5%
828
 
2.5%
408
 
2.5%
607
 
2.2%
417
 
2.2%
Other values (98)234
72.4%
ValueCountFrequency (%)
302
 
0.6%
321
 
0.3%
333
 
0.9%
349
2.8%
368
2.5%
ValueCountFrequency (%)
3291
 
0.3%
2991
 
0.3%
2521
 
0.3%
2031
 
0.3%
2024
1.2%

LOAD
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.1974401
Minimum179.7337494
Maximum292.5237427
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:32.289184image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum179.7337494
5-th percentile191.0587097
Q1235.9279251
median262.0897217
Q3269.5638428
95-th percentile282.1558716
Maximum292.5237427
Range112.7899933
Interquartile range (IQR)33.63591766

Descriptive statistics

Standard deviation27.49003851
Coefficient of variation (CV)0.1103142893
Kurtosis-0.2015756694
Mean249.1974401
Median Absolute Deviation (MAD)14.58752441
Skewness-0.8524820081
Sum80490.77315
Variance755.7022172
MonotonicityNot monotonic
2022-09-21T19:06:32.411218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
219.1692811
 
0.3%
210.43894961
 
0.3%
287.06307981
 
0.3%
286.95587161
 
0.3%
285.25817871
 
0.3%
280.1944581
 
0.3%
266.6198121
 
0.3%
265.30270391
 
0.3%
265.58245851
 
0.3%
265.0068971
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
179.73374941
0.3%
179.82098391
0.3%
179.8589021
0.3%
179.93511961
0.3%
180.10617071
0.3%
ValueCountFrequency (%)
292.52374271
0.3%
290.60467531
0.3%
290.40570071
0.3%
290.37130741
0.3%
288.23818971
0.3%

SOX
Real number (ℝ≥0)

Distinct254
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1833.30031
Minimum10
Maximum2482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:32.539225image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile1541.1
Q11651
median1804
Q32094
95-th percentile2336.9
Maximum2482
Range2472
Interquartile range (IQR)443

Descriptive statistics

Standard deviation381.4239253
Coefficient of variation (CV)0.2080531614
Kurtosis10.67276954
Mean1833.30031
Median Absolute Deviation (MAD)195
Skewness-2.433229497
Sum592156
Variance145484.2108
MonotonicityNot monotonic
2022-09-21T19:06:32.668982image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160213
 
4.0%
106
 
1.9%
17985
 
1.5%
17813
 
0.9%
17463
 
0.9%
21093
 
0.9%
20983
 
0.9%
17923
 
0.9%
15712
 
0.6%
23102
 
0.6%
Other values (244)280
86.7%
ValueCountFrequency (%)
106
1.9%
112
 
0.6%
14951
 
0.3%
15251
 
0.3%
15291
 
0.3%
ValueCountFrequency (%)
24821
0.3%
24751
0.3%
24491
0.3%
24141
0.3%
23971
0.3%

COAL FLOW
Real number (ℝ≥0)

UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean190.0611782
Minimum130.7405396
Maximum226.2332153
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:32.798981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum130.7405396
5-th percentile142.1273544
Q1178.2989807
median192.4747162
Q3205.2574158
95-th percentile224.462825
Maximum226.2332153
Range95.49267578
Interquartile range (IQR)26.95843506

Descriptive statistics

Standard deviation22.25605299
Coefficient of variation (CV)0.1170994161
Kurtosis-0.01180940084
Mean190.0611782
Median Absolute Deviation (MAD)13.86590576
Skewness-0.6001190738
Sum61389.76056
Variance495.3318945
MonotonicityNot monotonic
2022-09-21T19:06:32.922981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160.24737551
 
0.3%
175.85173031
 
0.3%
224.67237851
 
0.3%
224.80429081
 
0.3%
222.22613531
 
0.3%
216.44017031
 
0.3%
216.56054691
 
0.3%
206.34062191
 
0.3%
203.22842411
 
0.3%
199.27613831
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
130.74053961
0.3%
131.75834661
0.3%
133.60488891
0.3%
133.8333741
0.3%
134.22315981
0.3%
ValueCountFrequency (%)
226.23321531
0.3%
226.04891971
0.3%
225.31036381
0.3%
225.0464631
0.3%
224.91699221
0.3%

AIR FLOW
Real number (ℝ≥0)

HIGH CORRELATION

Distinct151
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean935.3343653
Minimum764
Maximum1086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:33.052983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum764
5-th percentile770.1
Q1856
median966
Q31004.5
95-th percentile1052.4
Maximum1086
Range322
Interquartile range (IQR)148.5

Descriptive statistics

Standard deviation86.63563108
Coefficient of variation (CV)0.09262530523
Kurtosis-1.080989847
Mean935.3343653
Median Absolute Deviation (MAD)57
Skewness-0.4401245278
Sum302113
Variance7505.732573
MonotonicityNot monotonic
2022-09-21T19:06:33.174947image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7688
 
2.5%
8577
 
2.2%
9897
 
2.2%
9786
 
1.9%
9486
 
1.9%
10146
 
1.9%
8565
 
1.5%
8585
 
1.5%
9775
 
1.5%
9885
 
1.5%
Other values (141)263
81.4%
ValueCountFrequency (%)
7641
 
0.3%
7673
 
0.9%
7688
2.5%
7694
1.2%
7701
 
0.3%
ValueCountFrequency (%)
10861
0.3%
10671
0.3%
10661
0.3%
10651
0.3%
10642
0.6%

APH-A-inlet-O2
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.124628761
Minimum1.775512934
Maximum6.191920757
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:33.309631image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1.775512934
5-th percentile2.111430192
Q12.511747837
median2.988306761
Q33.490730524
95-th percentile4.811655188
Maximum6.191920757
Range4.416407824
Interquartile range (IQR)0.978982687

Descriptive statistics

Standard deviation0.8309047984
Coefficient of variation (CV)0.265921126
Kurtosis1.129782244
Mean3.124628761
Median Absolute Deviation (MAD)0.4914426804
Skewness1.094738012
Sum1009.25509
Variance0.6904027841
MonotonicityNot monotonic
2022-09-21T19:06:33.450183image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.6450817581
 
0.3%
3.9893231391
 
0.3%
2.5359475611
 
0.3%
2.4855077271
 
0.3%
2.2851688861
 
0.3%
2.2674837111
 
0.3%
2.8107492921
 
0.3%
3.2809731961
 
0.3%
3.0698566441
 
0.3%
3.3840765951
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
1.7755129341
0.3%
1.8143829111
0.3%
1.853409291
0.3%
1.8983772991
0.3%
1.9449011091
0.3%
ValueCountFrequency (%)
6.1919207571
0.3%
6.163959981
0.3%
5.6925964361
0.3%
5.5810575491
0.3%
5.5474619871
0.3%

APH-B-inlet-O2
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.012168919
Minimum1.698701382
Maximum5.354305744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:33.584331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1.698701382
5-th percentile2.104239321
Q12.489782929
median2.909387112
Q33.367511749
95-th percentile4.412256718
Maximum5.354305744
Range3.655604362
Interquartile range (IQR)0.8777288198

Descriptive statistics

Standard deviation0.7047507468
Coefficient of variation (CV)0.2339678702
Kurtosis0.3767929664
Mean3.012168919
Median Absolute Deviation (MAD)0.4328315258
Skewness0.8415969742
Sum972.9305608
Variance0.496673615
MonotonicityNot monotonic
2022-09-21T19:06:33.710333image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.9144225121
 
0.3%
3.6672761441
 
0.3%
2.8381211761
 
0.3%
2.8952784541
 
0.3%
2.5575714111
 
0.3%
2.6210069661
 
0.3%
2.9026253221
 
0.3%
3.328058721
 
0.3%
2.9975719451
 
0.3%
3.1935691831
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
1.6987013821
0.3%
1.7032442091
0.3%
1.7855116131
0.3%
1.9256926771
0.3%
1.9418481591
0.3%
ValueCountFrequency (%)
5.3543057441
0.3%
5.3247742651
0.3%
5.0017957691
0.3%
4.9521350861
0.3%
4.8861718181
0.3%

APH-A-outlet-O2
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.267019702
Minimum2.925982952
Maximum7.331449509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:33.847334image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2.925982952
5-th percentile3.223829222
Q13.704240203
median4.144909859
Q34.64294076
95-th percentile5.9407269
Maximum7.331449509
Range4.405466557
Interquartile range (IQR)0.9387005568

Descriptive statistics

Standard deviation0.8074154325
Coefficient of variation (CV)0.1892223352
Kurtosis1.048130837
Mean4.267019702
Median Absolute Deviation (MAD)0.4696316719
Skewness1.007382697
Sum1378.247364
Variance0.6519196806
MonotonicityNot monotonic
2022-09-21T19:06:33.965298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.7746930121
 
0.3%
4.9935736661
 
0.3%
3.4172587391
 
0.3%
3.3105850221
 
0.3%
3.0922911171
 
0.3%
3.2208514211
 
0.3%
3.6232833861
 
0.3%
4.0947604181
 
0.3%
3.9240956311
 
0.3%
4.2452006341
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
2.9259829521
0.3%
2.9260983471
0.3%
2.9439482691
0.3%
2.9684524541
0.3%
2.9943985941
0.3%
ValueCountFrequency (%)
7.3314495091
0.3%
7.2220325471
0.3%
6.6969962121
0.3%
6.6268239021
0.3%
6.5681514741
0.3%

APH-B-outlet-O2
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.267019702
Minimum2.925982952
Maximum7.331449509
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:34.092298image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2.925982952
5-th percentile3.223829222
Q13.704240203
median4.144909859
Q34.64294076
95-th percentile5.9407269
Maximum7.331449509
Range4.405466557
Interquartile range (IQR)0.9387005568

Descriptive statistics

Standard deviation0.8074154325
Coefficient of variation (CV)0.1892223352
Kurtosis1.048130837
Mean4.267019702
Median Absolute Deviation (MAD)0.4696316719
Skewness1.007382697
Sum1378.247364
Variance0.6519196806
MonotonicityNot monotonic
2022-09-21T19:06:34.210332image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.7746930121
 
0.3%
4.9935736661
 
0.3%
3.4172587391
 
0.3%
3.3105850221
 
0.3%
3.0922911171
 
0.3%
3.2208514211
 
0.3%
3.6232833861
 
0.3%
4.0947604181
 
0.3%
3.9240956311
 
0.3%
4.2452006341
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
2.9259829521
0.3%
2.9260983471
0.3%
2.9439482691
0.3%
2.9684524541
0.3%
2.9943985941
0.3%
ValueCountFrequency (%)
7.3314495091
0.3%
7.2220325471
0.3%
6.6969962121
0.3%
6.6268239021
0.3%
6.5681514741
0.3%

NOX
Real number (ℝ≥0)

Distinct220
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean645.1145511
Minimum5
Maximum989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:34.335931image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile445.1
Q1560
median630
Q3764
95-th percentile874
Maximum989
Range984
Interquartile range (IQR)204

Descriptive statistics

Standard deviation165.5003027
Coefficient of variation (CV)0.2565440547
Kurtosis3.534633679
Mean645.1145511
Median Absolute Deviation (MAD)104
Skewness-1.184293198
Sum208372
Variance27390.35019
MonotonicityNot monotonic
2022-09-21T19:06:34.458932image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62012
 
3.7%
58
 
2.5%
5795
 
1.5%
8614
 
1.2%
6304
 
1.2%
8114
 
1.2%
7953
 
0.9%
5603
 
0.9%
5723
 
0.9%
6063
 
0.9%
Other values (210)274
84.8%
ValueCountFrequency (%)
58
2.5%
4111
 
0.3%
4261
 
0.3%
4271
 
0.3%
4302
 
0.6%
ValueCountFrequency (%)
9891
0.3%
9621
0.3%
9411
0.3%
9221
0.3%
9201
0.3%

APH OUTLET TEMP-PASSA
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132.4925833
Minimum123.6230748
Maximum147.1204224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:34.594365image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum123.6230748
5-th percentile126.4946259
Q1128.8385773
median131.194163
Q3135.6556422
95-th percentile141.9840373
Maximum147.1204224
Range23.49734751
Interquartile range (IQR)6.817064921

Descriptive statistics

Standard deviation4.864357316
Coefficient of variation (CV)0.03671418577
Kurtosis0.3675239353
Mean132.4925833
Median Absolute Deviation (MAD)2.81775411
Skewness0.8692218146
Sum42795.10441
Variance23.6619721
MonotonicityNot monotonic
2022-09-21T19:06:34.719331image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.82745871
 
0.3%
123.78792571
 
0.3%
138.37583411
 
0.3%
138.12493391
 
0.3%
137.90662641
 
0.3%
137.12191261
 
0.3%
136.8746441
 
0.3%
136.17366031
 
0.3%
136.05260211
 
0.3%
134.69700111
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
123.62307481
0.3%
123.78792571
0.3%
124.58874511
0.3%
124.6014761
0.3%
124.83075211
0.3%
ValueCountFrequency (%)
147.12042241
0.3%
147.07440191
0.3%
146.62510681
0.3%
146.56975811
0.3%
146.48634851
0.3%

APH OUTLET TEMP-PASSB
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct323
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.8611184
Minimum126.9053472
Maximum150.4699198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2022-09-21T19:06:34.841133image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum126.9053472
5-th percentile130.5052981
Q1132.3298518
median134.3119303
Q3139.0307592
95-th percentile145.0121429
Maximum150.4699198
Range23.56457265
Interquartile range (IQR)6.700907389

Descriptive statistics

Standard deviation4.834372151
Coefficient of variation (CV)0.03558319117
Kurtosis0.366054226
Mean135.8611184
Median Absolute Deviation (MAD)2.667055766
Skewness0.9263984428
Sum43883.14126
Variance23.37115409
MonotonicityNot monotonic
2022-09-21T19:06:34.964139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131.41848751
 
0.3%
126.90534721
 
0.3%
141.95614121
 
0.3%
141.70561731
 
0.3%
141.4724071
 
0.3%
140.76704921
 
0.3%
140.56937661
 
0.3%
139.62468471
 
0.3%
139.50464381
 
0.3%
138.51392111
 
0.3%
Other values (313)313
96.9%
ValueCountFrequency (%)
126.90534721
0.3%
127.0112891
0.3%
127.7673341
0.3%
127.85905971
0.3%
128.07904311
0.3%
ValueCountFrequency (%)
150.46991981
0.3%
150.31607061
0.3%
149.91998291
0.3%
149.8954011
0.3%
149.81722011
0.3%

Interactions

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2022-09-21T19:06:31.259297image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

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Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-21T19:06:35.233137image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-21T19:06:35.405283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-21T19:06:35.567283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-21T19:06:31.414680image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-09-21T19:06:31.620714image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

df_indexDUSTLOADSOXCOAL FLOWAIR FLOWAPH-A-inlet-O2APH-B-inlet-O2APH-A-outlet-O2APH-B-outlet-O2NOXAPH OUTLET TEMP-PASSAAPH OUTLET TEMP-PASSB
0190.80219.1692812058.0160.247375771.02.6450822.9144233.7746933.774693669.0128.827459131.418488
1244.00193.3370671905.0139.956100782.04.6430194.2944965.7549695.754969782.0129.108368132.330617
2344.90191.7974401866.0139.279434773.04.6152784.3643535.6112535.611253758.0132.004634134.760106
3440.12191.7059331870.0140.341476768.04.5225394.2746015.5758395.575839740.0131.639511134.136602
4540.00190.0050661887.0141.173676768.04.2305564.1135775.3364015.336401754.0131.172384133.700633
5641.00189.7526401806.0140.826996768.04.5249294.1938115.5852275.585227724.0130.728358133.301366
6740.00193.0090941824.0143.815170771.04.2272303.9606505.2907305.290730706.0130.654622133.195791
7841.00191.8589781854.0140.718246768.04.0444314.1275165.1608985.160898735.0130.117528132.558395
8941.00191.1045231865.0141.939819767.04.3613704.0813515.4040265.404026719.0129.291687131.804967
91044.20191.0536191865.0140.984940768.04.2122384.0903895.2560975.256097743.0128.896029131.466138

Last rows

df_indexDUSTLOADSOXCOAL FLOWAIR FLOWAPH-A-inlet-O2APH-B-inlet-O2APH-A-outlet-O2APH-B-outlet-O2NOXAPH OUTLET TEMP-PASSAAPH OUTLET TEMP-PASSB
313314180.0275.9331971602.0200.9203951060.02.7307823.0037253.7955493.795549620.0141.814143145.620738
314315183.0290.4057011602.0225.3103641066.02.0073092.0990383.0684983.068498620.0146.202092149.520752
315316190.0292.5237431602.0224.6092831064.02.0865782.1069273.1504983.150498620.0146.569758149.919983
316317202.0290.6046751602.0224.6458591067.02.4636382.2233143.5685803.568580620.0146.486348149.895401
317318202.0284.6138311602.0224.5147711062.02.8226722.2478653.8696783.869678620.0147.074402150.469920
318319202.0280.9919131602.0224.7563931058.02.6099542.8555973.7067303.706730620.0147.120422150.316071
319320202.0281.4149171602.0224.4682771065.02.5535512.7444993.6816423.681642620.0146.625107149.817220
320321252.0275.9797971602.0225.0464631053.02.9365832.9221963.9230843.923084620.0146.369191149.502660
321322299.0276.7704161602.0224.9169921047.02.8833612.9093874.0350634.035063620.0146.193136149.266301
322323193.0279.7819211602.0224.5024721055.02.8438703.0338443.7556153.755615620.0142.019068144.889893